# Copyright 2023 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

import logging
import re
from re import Match
from typing import Dict, List
from common.bigquery_type import BigQueryType
from common.file_reader import read

logger = logging.getLogger(__name__)


class DDLParser:

  def __init__(self, ddl_path):
    ddl: List[str] = read(ddl_path).split("\n")
    # We only care about the `CREATE TABLE` DDL
    if ddl[0].startswith("CREATE SCHEMA"):
      ddl = ddl[1:]

    self._schema: Dict[str, BigQueryType] = self._to_schema(ddl)
    self._fully_qualified_table_name = self._to_fully_qualified_table_name(
        ddl[0]
    )

  def get_schema(self) -> Dict[str, BigQueryType]:
    return self._schema

  def get_fully_qualified_table_name(self):
    return self._fully_qualified_table_name

  @staticmethod
  def _to_fully_qualified_table_name(ddl: str) -> str:
    match: Match = re.search("CREATE TABLE `(.*)`", ddl)
    if match:
      return match.group(1)

  @staticmethod
  def _to_schema(ddl: List[str]) -> Dict[str, BigQueryType]:
    ddl = [line.strip() for line in ddl]
    columns_start_index = ddl.index("(")

    try:
      columns_end_index = ddl.index(")")
    except ValueError:
      try:
        columns_end_index = ddl.index(");")
      except ValueError:
        raise ValueError(
            "Couldn't parse schema file. Make sure this file is generated by"
            " the response of `fetch_bigquery_table_schema.py`"
        )

    if "PRIMARY KEY" in ddl[columns_end_index - 1]:
      columns_end_index -= 1

    schema = ddl[columns_start_index + 1 : columns_end_index]

    return DDLParser._to_dict(schema)

  @staticmethod
  def _to_dict(schema):
    d = {}
    for column in schema:
      column = DDLParser._strip_trailing_comma(column.strip())
      name: str = DDLParser._column_name(column)

      if DDLParser._is_metadata_column(name):
        logger.debug(f"Skipping metadata column {column}")
        continue

      try:
        source_type: BigQueryType = DDLParser._column_schema(column)
      except ValueError:
        raise ValueError(
            "Expected column description to in the format of '<column_name>"
            f" <column_type>' but got: '{column}'"
        )
      d[name] = source_type

    return d

  @staticmethod
  def _strip_trailing_comma(s: str):
    return s[:-1] if s[-1] == "," else s

  @staticmethod
  def _is_metadata_column(column: str):
    return column.startswith("_metadata_") or column == "datastream_metadata"

  @staticmethod
  def _column_schema(column: str) -> BigQueryType:
    column_schema = column.split()[1:]
    if column_schema[0].startswith("NUMERIC"):
      return BigQueryType.NUMERIC
    elif column_schema[0].startswith("BIGNUMERIC"):
      return BigQueryType.BIGNUMERIC
    elif column_schema[0].startswith("STRING"):
      return BigQueryType.STRING
    else:
      return BigQueryType(column_schema[0])

  @staticmethod
  def _column_name(column: str):
    return column.split()[0].strip("`")